Inventory management with random supply and imperfect information: A hidden Markov model

In most of the papers on inventory models operating in a random environment, the state of the environment in each period is assumed to be fully observed with perfect information. However, this assumption is not realistic in most real-life situations and we provide a remedy in this paper by assuming that the environment is only partially observed with imperfect information. We accomplish this by analyzing two formulations of single-item models with periodic-review and random supply in a random environment. In the first one, supply is random due to random capacity of production and random availability of transportation. We show that state-dependent base-stock policy is optimal if the capacity and all costs are observed, while demand and availability are unobserved. In the second model, we consider a model with random availability only with fixed-ordering cost. We show that state-dependent (s,S) policy is optimal if the availability process is observable.     

An Application of Value-of-Information to Decision Process Reengineering

Value of information (VOI) methods were used to guide changes to recurrent organizational decision processes under a reengineering effort at a major automobile manufacturer to reduce supply and demand imbalances involving capacity for parts and products. We modeled representative decisions assuming that they would be made with and without the benefit of improved information flows and calculated the resulting increase in expected value. By factoring in the entire range of decisions affected by a process change, we scaled the value of each organizational change to a life cycle value. The results quantified the impact of organizational changes in order to refine and prioritize a portfolio of change projects.     

Building competences for new customer value creation: An exploratory study

Recent marketing literature suggests companies to become market driving (proactive business logic, changing the rules of the market) instead of market driven (reactive business logic, customer-led). This transformation implies that companies are able to boost their capacity to create new customer value. Based on survey data of business-to-business markets, we advance a tentative model that links competence development to new customer value creation. Although exploratory in its nature, our study exhibits that companies should build three types of competences: marketing practices for external knowledge absorption, general organizational competences and supply chain/network competences. Using cluster analysis, we are able to further link these competences to the capacity of new value creation. Four clusters are detected with different degrees of expertise in new value creation and each displaying their own profile of competences. Becoming market driving requires an integrated and balanced view on marketing practices.     

Production planning and inventory allocation of a single-product assemble-to-order system with failure-prone machines

We consider the optimal production and inventory allocation of a single-product assemble-to-order system with multiple demand classes and lost sales. Each component is replenished by a dedicated machine that is subjected to unpredictable breakdowns. We find that the machine state not only influences the production and allocation decisions on its own component but also influences the decisions on the other components. Specifically, the optimal component production policy is a base-stock policy with the base-stock level non-decreasing in the inventory levels of the other components and the states of the other machines. The optimal component allocation policy is a rationing policy with the rationing level non-increasing in the inventory levels of the other components, the states of the other machines, and its own machine state. We use an exponential distribution to approximate the distribution of the total processing times and propose two heuristic policies to address the production and allocation decisions. The importance of taking machine failures into consideration is revealed through computational experiments.     

Supply network capacity planning for semiconductor manufacturing with uncertain demand and correlation in demand considerations

A semiconductor supply network involves many expensive steps, which have to be executed to serve global markets. The complexity of global capacity planning combined with the large capital expenditures to increase factory capacity makes it important to incorporate optimization methodologies for cost reduction and long-term planning. The typical view of a semiconductor supply network consists of layers for wafer fab, sort, assembly, test and demand centers. We present a two-stage stochastic integer-programming formulation to model a semiconductor supply network. The model makes strategic capacity decisions, (i.e., build factories or outsource) while accounting for the uncertainties in demand for multiple products. We use the model not only to analyze how variability in demand affects the make/buy decisions but also to investigate how the correlation between demands of different products affects these strategic decisions. Finally, we demonstrate the value of incorporating demand uncertainty into a decision-making scheme.     

The role of ERP tools in supply chain information sharing,cooperation, and cost optimization

The transaction based integrated Enterprise Resource Planning (ERP) software provides different tools that can support supply chain integration but at the same time it has several features that obstructs the integration with business partners. We concentrate on the inventory management aspects of supply chain coordination reviewing the recent quantitative modeling and organizational results available in literature. We summarize the results of a detailed numerical and sensitivity analysis based on our previously published models for supply chain cooperation and joint optimal ordering and shipment policies for the buyer and supplier. These results can be used in enterprise software to measure the potential monetary value of policy coordination, to promote cooperation, and minimize the total supply chain system cost. Our further goal is to combine quantitative tools with organizational and management factors, and to integrate them in a multi-level framework of policy coordination.     

技术能力对供应链信息共享程度的影响研究

信息共享是进行供应链管理的基础,也是影响供应链协调的关键决定因素。本文将技术能力用技术应用情况和技术联盟程度表示,将信息共享程度用信息共享质量和信息共享内容表示,通过问卷调查并运用结构方程模型进行实证研究。结果表明：技术联盟和技术应用对供应链信息共享质量和内容均有显著的正向影响;相较于技术应用,技术联盟对供应链信息共享质量和内容的影响更为显著。供应链企业应通过提高技术能力促进企业间信息共享,从而为实现供应链协调奠定基础。     

基于PSM-DID模型的政策对试点企业经营绩效的影响评价研究——以"供应链创新与应用试点"政策为例

近年来,我国政府积极推进供应链领域政策的制定与发布,如何更好地评估既有政策带来的绩效成为政府进一步完善供应链相关政策的关键。本文选取商务部“供应链创新与应用试点”政策(商建函[2018]142号)作为研究对象,并构建双重差分倾向得分匹配(PSM-DID)模型,将试点企业经营绩效中的盈利能力指标ROA作为被解释变量,利用Stata15.0对2015~2019年5年间覆盖3494家样本企业的面板数据,共15278个样本进行处理计算,以此对该政策实施对试点企业经营绩效的影响效果进行评价。结果表明:2018年开始实施的供应链创新与应用试点政策,对试点企业的经营绩效ROA有着显著的正向促进作用。此外,企业规模、企业的资产负债率、托宾Q值和企业固定资产投资比率都对ROA有显著影响。其中企业规模和托宾Q值对ROA有正向影响,资产负债率和固定资产投资比率对ROA有负向影响。     

Base-stock policies for the lost sales inventory system with Poisson demand and Erlangian lead times

The base-stock policies for the studied inventory system can easily be evaluated through Erlang's loss formula when the lead times are mutually independent. This is often the case only if the base-stock $S$ is one. If $S$ is larger than one, the Erlangian lead times become stochastically dependent under the realistic assumption that the replenishment orders do not cross in time. We make this assumption and show for any positive $S$ that the number of replenishment orders outstanding has an equilibrium distribution which is a slightly modified truncated version of a negative binomial distribution. It turns out to be easy to compute the stock-out frequency recursively for $S=1,2,\dots .$ For each $S$, the average stock can be specified in terms of this frequency. We prove that the frequency is convex in $S$. It is therefore straightforward to compute the base-stock for which the average cost is minimized and to compute the minimum average cost. Our numerical study illustrates that the minimum average cost is very sensitive to the shape parameter describing the Erlangian lead times, which is in sharp contrast to the complete insensitivity when lead times are independent.     

Solutions for flexible container leasing contracts with options under capacity and order constraints

The container–shipping market becomes prosperous with the development of the global economy. As shipping networks become more complex and heterogeneous, container capacity planning becomes more difficult. This paper tackles the container planning problem from the carrier’s perspective in a two-echelon container shipping service chain (CSSC), which includes one carrier and one upstream rental company. A flexible contract with options is introduced into the one-period container planning mechanism. With the flexible options contract, the rental company requires the carrier to make a commitment or place an order in advance. Options give buyer the right to modify the initial orders to better match the supply with the demand. Based on the carrier’s decision tendency, i.e., aggressive or conservative, we analyze the application strategies of the unilateral options and the bidirectional options in different practical scenarios. In particular, for the applicability of the decision models, we further consider the shipping capacity and the minimum order constraints and formulate the carrier’s option policies with constrained nonlinear programs. Numerical examples show that the proposed decision strategies with option contract cannot only effectively increase the container trading quantity between the rental company and the carrier, but also significantly reduce the carrier’s container capacity risk while increasing its profit.     

Dark Fiber Valuation

Valuation of dark fiber has recently generated controversy, sparked particularly by the large sums booked for swaps of dark fiber between companies. One of the issues raised is valuation: i.e., what is the value of an asset that generates no revenue now and may do so at some unknown point in the future but only after investment, in an uncertain business climate, and where prices are dropping? The picture is further complicated because the result of investing to bring the asset to market (i.e. lighting the fiber) changes the supply and demand conditions of the market itself and hence invalidates price predictions. A realistic and consistent valuation methodology is necessary for increasingly cautious companies, auditors, and investors. In this paper we describe such a valuation methodology for dark fibre based on real options. Publicly available bandwidth price services start to make this practical by providing market price information. For dark fibre valuation the real option to be valued are the lighting decisions. We specifically include the effect on the market of adding new capacity by using the price-elasticity of demand within the stochastic price process itself, conditional on lighting decisions. Prices are generally volatile and decreasing with time. The evolution of lighting costs and maintenance are included in the valuation. The real options technique used here is novel in that it combines economic and market factors explicitly with mathematical finance to arrive at a valuation and optimal decisions. We found that the optimal lighting riming and capacity decisions to depend on many of the factors included in the analysis with no simple triggers: the details really matter.     

Does social capital matter for supply chain resilience? The role of absorptive capacity and marketing-supply chain management alignment

Marketing in an increasingly tumultuous marketplace requires resilience -the ability to withstand, adapt, and flourish despite turmoil and adverse change- that extends beyond firm boundaries. Although external resources are arguably essential to achieve resilience, little is known how and when firms' social capital derived from interorganizational relationships can lead to supply chain resilience. Therefore, we investigate the role of absorptive capacity and marketing-supply chain management alignment in realizing the potential impact of social capital on supply chain resilience. Using data obtained from dual respondents from 265 Turkish firms, we test the mediating role of absorptive capacity and the moderating role of marketing-supply chain management alignment. Our findings indicate absorptive capacity mediates the relationship between social capital and supply chain resilience, and the links between social capital and absorptive capacity and social capital and supply chain resilience are stronger when marketing-supply chain management alignment is high. We also find that supply chain resilience is positively associated with organizational performance, empirically supporting the proposed value of supply chain resilience for firm strategy. Accordingly, our paper highlights that both absorptive capacity and marketing-supply chain management alignment are necessary to realize the actual value of social capital for supply chain resilience and ensuing performance.     

Information and reputation mechanisms in auctions of remanufactured goods

We investigate how feedback scores and alternative reputation mechanisms can mitigate asymmetric information in auctions of second-hand electronic items. In contrast to previous studies, we exploit the information available across heterogeneous goods and avoid the problems caused by different degrees of wear and tear by studying remanufactured products. We find the presence of relevant scale effects in the value of such reputation mechanisms that become complements or substitutes depending on the value of the transactions. Feedback scores are not valuable when alternative contractual devices are in place, such as refurbishment by a manufacturer-approved vendor and the availability of return policies. However, when we partition the sample according to the value of the auctions, feedback scores become effective for cheap items, whereas return policies are important for expensive goods.     

The fates of De Novo and De Alio producers in the American Automobile Industry 1885–1981

Do laterally diversifying firms outlast new startups? Or does organizational inertia give the advantage to startups? We explore these questions here using the experiences of American automobile manufacturers from 1885 through 1981. We advance and test an integrative model that allows the organizational effects of entry mode to vary across the firm's life cycle. We also compare the life chances of laterally diversifying firms by industry of origin, including especially bicycle, carriage and engine manufacturers. Findings show the potentially integrative value of an evolutionary approach to strategy.     

Wie viel Europa braucht die Energiewende?

It is often argued that Germany’s energy transition (the so-called “Energiewende”) needs to be “Europeanized”, so as to make the transition process more efficient. In particular, the German system of feed-in tariffs for renewables is criticized for being an obstacle to efficient European energy supply. However, we point out that Germany’s approach is no outlier but rather well embedded in the European context of heterogeneous energy policies. Also, full centralization and harmonization of political decisions on the EU-level may not be desirable in many fields of energy policy beyond climate protection if the full economic costs of energy supply are taken into account. In addition, legal and politico-economic constraints need to be considered. Against this background, we identify priorities for fostering the European dimension of the Member States’ energy policies, such as the coordination of grid extensions and capacity markets.     

Retailer policy, uncertainty reduction, and supply chain performance

We investigate how the retailer’s inventory policy affects the total cost of a serial supply chain. When the retailer uses the locally optimal (s,S) policy, there is randomness in order time and order quantity to the supplier whereas the supplier sees randomness only in order quantity for the suboptimal (R,T) policy and only in order time for another suboptimal (Q,r) policy. Using an extensive computational study, we find that the suboptimal policies perform better from the total supply chain perspective. The benefit of policy changes is magnified when the retailer costs are low, when the supplier costs are high, and when there is information sharing.     

Coordinating a one-warehouse N-retailer distribution system under retailer-reporting

We consider a distribution system consisting of a System Administrator (SA) and N retailers managed under dynamic allocation and static routing policies. We study the system under two scenarios: (a) the up-to-date information scenario, under which the SA has access to the inventory levels at the retailers in real time and makes the replenishment and allocation decisions based on these information, aiming to minimize total supply chain cost; (b) the retailer-reporting scenario, under which the SA makes the replenishment and allocation decisions based on the information reported by the retailers. Under the retailer-reporting scenario, the retailers compete against each other by reporting their inventory levels falsely to get the desired allocations, which minimize the retailers’ expected cost. For N=2 retailers, we show that, in general, reporting truthfully does not minimize either retailer's expected cost/cycle over their respective replenishment/allocation cycles, and that the sum of the retailers' expected cost/cycle is strictly greater than in the up-to-date information scenario. We then show that by including a particular transfer-payment between the two retailers, truth-telling is a Bayesian equilibrium, and that the same system expected cost/period as in up-to-date information scenario can be achieved.     

Inter-temporal inventory competition and the effects of capacity constraints

This paper addresses an intertemporal inventory competition between a supplier (a provider, manufacturer) and a retailer engaged in a supply chain. The paper's focus is on the effect of capacity constraints on both parties when demands are seasonal. The paper provides a comparative study of two solution approaches, one is based on supply chain competition and the other is based on system wide optimization. Our results demonstrate that with dynamic inventory competition, the retailer reduces inventory costs by reducing the response period to higher demands while increasing the supply requests compared to the system-wide optimal approach. As a result, the supplier's inventory costs increase. An example illustrating these particular facets of the problem and its application is presented and discussed in light of the supplier and the retailer coordinating policies.     

The value of relational learning in global buyer‐supplier exchanges: a dyadic perspective and test of the pie‐sharing premise

Research in collaborative interorganizational relationships has typically focused on the value of these relationships to a specific supply chain partner. Furthermore, the phenomenon has rarely been explored in a global setting. Using primary data from 126 cross‐border dyads, we investigate the influence of relational learning on the relationship performance of both the buyer and the supplier, testing the contention that both members (1) benefit from relational learning efforts and (2) enjoy equal pieces of the benefits pie. We find that three specific types of relational learning (information sharing, joint sensemaking, and knowledge integration) influence relationship performance, and that these dimensions of relational learning affect supply chain partners in different ways. We draw conclusions regarding the relative value of relational learning for both buyers and suppliers. Copyright © 2011 John Wiley & Sons, Ltd.     

Trading reserved capacity independently among supply chains

We propose a novel mechanism for pooling the reserved capacity (super capacity) of different supply chains, so that they can more effectively match their single-period inventory supplies with their demands. Through this mechanism, retailers can buy or sell unutilized super capacity independently as a commodity in a sub-industry before and during the selling season, which helps improve supply flexibility and increase the utilization of suppliers' reserved capacity. Our findings provide a new channel coordination strategy for a group of supply chains to hedge against capacity and inventory risks by trading super capacity with their competitors, which yields individual and aggregate benefits.